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Drawing from resource-based theorising, the concept of network embeddedness and a process perspective on entrepreneurship, this paper establishes a conceptual framework to explain a multi-level and multi-locational network embeddedness of creative entrepreneurs in non-urban places. It challenges stylised facts about creative entrepreneurship as a predominantly urban phenomenon.

Based upon the conceptual framework for creative entrepreneurship in a non-urban place, an illustrative case study of small-scale creative-design entrepreneurs on the Lofoten Islands in Norway (2019) is utilised to discuss the framework.

The conceptual paper derives a fine-grained understanding about how creative entrepreneurship emerges and develops in non-urban places and contributes to a better understanding of how such places can nurture such entrepreneurship through multiple network embeddedness and resource-exchange configurations.

The article will enable further empirical research that tests, validates and, if necessary, refines the framework established.

Creative entrepreneurs should use various resource-exchange combinations with diverse networks to become locally embedded in non-urban places. Public-policy managers need to be aware of this variety that may exist with the network embeddedness of such entrepreneurs to support them and develop the location through resource provisions.

The paper uses an original conceptual framework.

The purpose of this paper is to substantiate the importance of an educational platform for digital modernization of modern Russia’s regions in Industry 4.0 and to determine the functions and conceptual foundations of organization of regional market of educational services for execution of functions for stimulation of digital modernization of Russia’s regional economy.

The authors use the method of regression analysis for studying the influence of the indicators of adaptation of the market of educational services to the conditions of Industry 4.0 on efficiency of digital modernization of economy of the regions of the Volga Federal District of the Russian Federation as of late 2018-early 2019. The information and empirical basis of the paper is materials of the index “Digital Russia” of the Moscow School of Management “Skolkovo.”

It is determined that the market of educational services plays an important role in the process of transition of regions of modern Russia to Industry 4.0, performing two functions: training of personnel who are capable of working with digital technologies and training of personnel who are capable of creating new digital technologies at a region’s companies. As a result, the educational platform of digital modernization of the regional economy is formed. The developed conceptual foundations of an organization of the regional market of educational services for execution of its functions on stimulating the digital modernization of Russia’s regional economy allow for three variants of the process of training of personnel: within execution of the order of partner companies in a regional technological park, within participation of the region’s companies in a tender for training of personnel and within an independent initiation of the process of training of personnel by universities based on the results of digital marketing.

The offered authors’ recommendations ensure the following advantages during the creation and development of the educational platform of a region’s digital modernization in Industry 4.0: high marketing activity of universities, direct sequence of training of personnel and improved treatment of the effectiveness of regional universities as the ratio of efficiency in personnel training to expenditures, which stimulates competition between universities and maximization of effectiveness of educational platform of a region’s digital modernization in Industry 4.0.

The purpose of the research is to study the consequences of total (comprehensive) automatization of entrepreneurship for interested parties through the prism of competition human and artificial intellectual capital in production and distribution in Industry 4.0.

The research is conducted with application of scenario analysis, regression analysis, imitation modeling, forecasting and non-linear multi-parametric optimization with the simplex method.

The authors perform scenario modeling of competition between human and artificial intellectual capital in production and distribution in Industry 4.0 and offer recommendations for pro-active management of competition between human and artificial intellectual capital in production and distribution in Industry 4.0.

Contrary to the existing approach to studying competition between human and artificial intellectual capital in Industry 4.0, automatization of distribution, not production, is most preferable. This shows increase of the value of human intellectual capital in distribution during its automatization based on AI. This is an unprecedented and breakthrough conclusion for the modern economic science. It allows creating a completely new direction of research of competition between human and artificial intellectual capital in production and distribution in Industry 4.0, in which optimization of social consequences is achieved not by means of restraint of automatization but by means of its stimulation. The key condition is stimulation of automatization of distribution with limited automatization of production. Based on this conclusion, it is recommended to continue research in continuation of the presented work.

The purpose of the research is to determine the perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 and to develop scientific and methodological recommendations for their implementation. For this, the directions of state regulation of competition between human and artificial intellectual capital are described, monitoring of competition between human and artificial intellectual capital by the example of modern Russia (2019) is performed and scientific and practical recommendations for state regulation of competition between human and artificial intellectual capital are developed, with their approbation by the example of modern Russia (2019).

A method of expert evaluation is used for collection of the information and empirical data. The method of comparative analysis is used for comparing the successfulness of implementing the distinguished directions of state regulation of competition between human and artificial intellectual capital (4.1) according to the official statistics to their current evaluation according to the interested parties. Also, future evaluation (forecasts) according to the interested parties (until 2045) is determined.

It is substantiated that during evaluation of state regulation of competition between human and artificial intellectual capital in Industry 4.0, one cannot use only the official statistics, as these data are fragmentary and indirect. Fuller and more precise data are provided by assessment according to the interested parties. They allow determining the current and the future state of affairs and, based on it, compiling a forecast and developing a long-term strategy of state regulation of competition between human and artificial intellectual capital in Industry 4.0.

The perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 are as follows: stimulation of competition in the market of intellectual capital, social risk management of the market of intellectual capital, managing international competition in the market of intellectual capital and ecological risk management of the intellectual capital market. As the experience of modern Russia shows, even at the initial stage of transition to Industry 4.0, the measures of state regulation of competition between human and artificial intellectual capital are not enough, but their deficit is moderate. In the course of development of Industry 4.0, the necessity for the measures of regulation will grow, and their deficit will increase. That's why there's a need for strategic approach to their implementation, which envisages their systemic reconsideration and supplementing. An author's algorithm is offered for this.

The purpose of the paper is to develop a concept of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital.

The methods of regression and correlation analysis are used. The role of human and artificial intellectual capital for provision of effectiveness and competitiveness of the system of science and education is determined, as well as its correspondence to the modern challenges. Analysis of perspectives and limitations of automatization of the system of science and education based on AI is conducted; a model of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital is compiled.

It is established that in the system of science and education, the decisive production factor is intellectual capital, but human intellect does not necessarily have to dominate in its structure. AI is one of the most popular technologies of Industry 4.0 in the system of science and education, which has wide perspectives of practical implementation. As experience of the leading world universities, which had the highest level of digitization in 2018, showed, foundation on non-breakthrough digital technologies (computer equipment and Internet) does not allow opening the potential of increase of indicators of effectiveness and competitiveness of the system of science and education and bringing it in correspondence to the modern challenges based on digitization. However, correlation of activity of application of artificial intellectual capital with these indicators is four times higher (0.2), as compared to correlation of these indicators with activity of application of human intellectual capital (0.05). This shows demand for digitization of the system of science and education, but based on breakthrough digital technologies, of which AI should become the key one.

It is substantiated that higher education could be automatized based on AI by 85% and science by 63%. Therefore, on the whole in the system of science and education, the share of AI in the structure of intellectual capital could reach 74% ((85 + 63)/2). It is recommended to use the developed model of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital.

The purpose of this article is to determine the future proportion and variants of usage of human intellect and artificial intelligence (AI) in entrepreneurship of industry 4.0 that fits social entrepreneurship the most. It could be convergence (simultaneous utilization during the same entrepreneurial processes with the emphasis on unique features by the terms of the competition) or divergence (usage during different business processes by the terms of labor division).

The authors determine the influence of usage of human capital and AI on the efficiency of social entrepreneurship. The authors identify the perspective directions of usage of AI in social entrepreneurship and evaluate the readiness and interest in the implementation of these directions of concerned parties. The authors also model the optimal proportions and the variant of usage of human intellect and AI in social entrepreneurship in the conditions of Industry 4.0 in the future (until 2030).

It is found that social entrepreneurship will use the opportunities of Industry 4.0 for optimization of its activities until 2030, but will refuse from full automatization, using human intellect and AI at the same time.

The most perspective directions of application of AI at social companies are a collection of social goods and services, marketing studies and promotion of social goods and services. Neither convergence nor divergence of human and artificial intellectual capital does not fully conform to the interests of concerned parties. The most preferable (optimal) variant of usage of human intellect and AI in social entrepreneurship in the Industry 4.0 is human intelligent decision support.

The purpose of this paper is to determine the priorities of formation of competencies during training of digital personnel for industry 4.0.

The author performs two experiments for determining the scenario according to which industry 4.0 develops and will develop: the first experiment is aimed at determining the influence of the number of robots at unemployment level in 2019 and 2022 with the help of regression and correlation analysis (regression curves are built). The second experiment is connected to evaluation of the ratio of the number of robots to the number of population in 2019 and 2022. The research objects are countries with the highest number of robots in the world – i.e. with the highest level of development of industry 4.0; the information and empirical basis is materials of the International Federation of Robotics and the International Monetary Fund for 2019 and their forecasts for 2022.

The results of the performed experiments showed that in 2019 and 2022 the level of robotization of socio-economic systems of the countries of the world will be very low, and robotization will not cause growth of unemployment. Based on this, it is concluded that industry 4.0 will be developing according to the scenario of moderate automatization and robotization with preservation of domination of human labor in most business processes and spheres of economy. Communications with people will constitute the basis of the activities of digital personnel, and social competencies (with obvious significance of technical competencies) will be of top priority for them.

It is substantiated that technical competencies, with their large importance, will move to the background, while the key task will be society’s adaptation to the new technological mode and making social competencies the highest priority. The social and technical competencies of digital personnel in view of the performed tasks for industry 4.0 are determined.